mcp-server-webcrawl 0.11.2

MCP server for search and retrieval of web crawler content

mcp-server-webcrawl

Advanced search and retrieval for web crawler data. With mcp-server-webcrawl, your AI client filters and analyzes web content under your direction or autonomously. The server includes a full-text search interface with boolean support, and resource filtering by type, HTTP status, and more.

mcp-server-webcrawl provides the LLM a complete menu with which to search your web content, and works with a variety of web crawlers:

Crawler/Format	Description	Platforms	Setup Guide
WARC	Standard web archive format	varies by client	Setup Guide
wget	Command-line website mirroring tool	macOS/Linux	Setup Guide
InterroBot	GUI crawler and analyzer	macOS/Windows	Setup Guide
Katana	Security-focused crawler	macOS/Windows/Linux	Setup Guide
SiteOne	GUI crawler and analyzer	macOS/Windows/Linux	Setup Guide

mcp-server-webcrawl is free and open source, and requires Claude Desktop and Python (>=3.10). It is installed on the command line, via pip install:

pip install mcp-server-webcrawl

For step-by-step MCP server setup, refer to the Setup Guides.

Features

• Claude Desktop ready
• Multi-crawler compatible
• Filter by type, status, and more
• Boolean search support
• Support for Markdown and snippets
• Roll your own website knowledgebase

Prompt Routines

mcp-server-webcrawl provides the toolkit necessary to search web crawl data freestyle, figuring it out as you go, reacting to each query. This is what it was designed for.

It is also capable of running routines (as prompts). You can write these yourself, or use the ones provided. These prompts are copy and paste, and used as raw Markdown. They are enabled by the advanced search provided to the LLM; queries and logic can be embedded in a procedural set of instructions, or even an input loop as is the case with Gopher Service.

Prompt	Download	Category	Description
🔍 SEO Audit	auditseo.md	audit	Technical SEO (search engine optimization) analysis. Covers the basics, with options to dive deeper.
🔗 404 Audit	audit404.md	audit	Broken link detection and pattern analysis. Not only finds issues, but suggests fixes.
⚡ Performance Audit	auditperf.md	audit	Website speed and optimization analysis. Real talk.
📁 File Audit	auditfiles.md	audit	File organization and asset analysis. Discover the composition of your website.
🌐 Gopher Interface	gopher.md	interface	An old-fashioned search interface inspired by the Gopher clients of yesteryear.
⚙️ Search Test	testsearch.md	self-test	A battery of tests to check for Boolean logical inconsistencies in the search query parser and subsequent FTS5 conversion.

If you want to shortcut the site selection (one less query), paste the markdown and in the same request, type "run pasted for [site name or URL]." It will figure it out. When pasted without additional context, you should be prompted to select from a list of crawled sites.

Boolean Search Syntax

The query engine supports field-specific (field: value) searches and complex boolean expressions. Fulltext is supported as a combination of the url, content, and headers fields.

While the API interface is designed to be consumed by the LLM directly, it can be helpful to familiarize yourself with the search syntax. Searches generated by the LLM are inspectable, but generally collapsed in the UI. If you need to see the query, expand the MCP collapsable.

Example Queries

Query Example	Description
privacy	fulltext single keyword match
"privacy policy"	fulltext match exact phrase
boundar*	fulltext wildcard matches results starting with boundar (boundary, boundaries)
id: 12345	id field matches a specific resource by ID
url: example.com/somedir	url field matches results with URL containing example.com/somedir
type: html	type field matches for HTML pages only
status: 200	status field matches specific HTTP status codes (equal to 200)
status: >=400	status field matches specific HTTP status code (greater than or equal to 400)
content: h1	content field matches content (HTTP response body, often, but not always HTML)
headers: text/xml	headers field matches HTTP response headers
privacy AND policy	fulltext matches both
privacy OR policy	fulltext matches either
policy NOT privacy	fulltext matches policies not containing privacy
(login OR signin) AND form	fulltext matches fullext login or signin with form
type: html AND status: 200	fulltext matches only HTML pages with HTTP success

Field Search Definitions

Field search provides search precision, allowing you to specify which columns of the search index to filter. Rather than searching the entire content, you can restrict your query to specific attributes like URLs, headers, or content body. This approach improves efficiency when looking for specific attributes or patterns within crawl data.

Field	Description
id	database ID
url	resource URL
type	enumerated list of types (see types table)
size	file size in bytes
status	HTTP response codes
headers	HTTP response headers
content	HTTP body—HTML, CSS, JS, and more

Content Types

Crawls contain resource types beyond HTML pages. The type: field search allows filtering by broad content type groups, particularly useful when filtering images without complex extension queries. For example, you might search for type: html NOT content: login to find pages without "login," or type: img to analyze image resources. The table below lists all supported content types in the search system.

Type	Description
html	webpages
iframe	iframes
img	web images
audio	web audio files
video	web video files
font	web font files
style	CSS stylesheets
script	JavaScript files
rss	RSS syndication feeds
text	plain text content
pdf	PDF files
doc	MS Word documents
other	uncategorized

Extras

The extras parameter provides additional processing options, transforming HTTP data (markdown, snippets, xpath), or connecting the LLM to external data (thumbnails). These options can be combined as needed to achieve the desired result format.

Extra	Description
thumbnails	Generates base64 encoded images to be viewed and analyzed by AI models. Enables image description, content analysis, and visual understanding while keeping token output minimal. Works with images, which can be filtered using type: img in queries. SVG is not supported.
markdown	Provides the HTML content field as concise Markdown, reducing token usage and improving readability for LLMs. Works with HTML, which can be filtered using type: html in queries.
snippets	Matches fulltext queries to contextual keyword usage within the content. When used without requesting the content field (or markdown extra), it can provide an efficient means of refining a search without pulling down the complete page contents. Also great for rendering old school hit-highlighted results as a list, like Google search in 1999. Works with HTML, CSS, JS, or any text-based, crawled file.
xpath	Extracts XPath selector data, used in scraping HTML content. Use XPath's text() selector for text-only, element selectors return outerHTML. Only supported with type: html, other types will be ignored. One or more XPath selectors (//h1, count(//h1), etc.) can be requested, using the extrasXpath argument.

Extras provide a means of producing token-efficient HTTP content responses. Markdown produces roughly 1/3 the bytes of the source HTML, snippets are generally 500 or so bytes per result, and XPath can be as specific or broad as you choose. The more focused your requests, the more results you can fit into your LLM session.

The idea, of course, is that the LLM takes care of this for you. If you notice your LLM developing an affinity to the "content" field (full HTML), a nudge in chat to budget tokens using the extras feature should be all that is needed.